Application of Image Color Gamut Boundary Judgment Algorithm in Digital Media

Table 2

Algorithm distribution of image gamut boundary.

Algorithm text	Image gamut boundary code
Their original images form	For i in range(k):
Causing the image color gamut	Getlabel = labels[sortdisindex[i]]
The image color	Classcount[getlabel] = classcount.get(getlabel, 0) +1
Time being too long and	Datasize = data.shape[0]
The continuous experiment	X = np.tile(inputx, (datasize, 1)) - data
Gamut boundary	Xpositive = x 2
The image color gamut	Xdistances = xpositive.sum(axis=1)
Test image pairs twice to	Distances = np.sqrt(xdistances)
Observers evaluate the	Print(sortclass[0][0])
Test image pairs	Knnclassify(inputx, data, labels, k)
Test images and	Return sortclass[0][0]